Aggregator FAQs

Question 1

What is Aggregator and what does it do?

Accepted Answer

Aggregator is a software tool designed to collect and unify capabilities from various MCP (Multi-Agent Communication Protocol) servers. It stores this aggregated tool metadata in a vector database (like Pinecone), enabling Large Language Models (LLMs) to efficiently search, discover, and utilize a collective set of tools from a single point.

Question 2

How do I set up and run Aggregator?

Accepted Answer

To get started, you need to configure your MCP server URLs and Pinecone API credentials in a `.env` file. After installing dependencies with `uv`, you can launch the server using Uvicorn. LLMs or clients can then query the aggregator's API endpoint to search for and use tools.

Question 3

Can Aggregator be used with any LLM?

Accepted Answer

Yes, Aggregator is designed to be highly versatile. Any Large Language Model or AI agent that can make HTTP requests or structured tool calls can interact with Aggregator by providing a search query. It acts as an intelligent intermediary, connecting LLMs to a wide range of aggregated tools.

Question 4

How does Aggregator enhance LLM performance?

Accepted Answer

By consolidating tools from multiple MCP servers into a single, searchable vector database, Aggregator significantly improves an LLM's ability to find and invoke the most relevant tools across different systems. This leads to more efficient tool utilization, better decision-making, and enhanced overall performance for AI agents.

Question 5

What are the key features of Aggregator?

Accepted Answer

Aggregator offers aggregated tool discovery from multiple MCP servers, seamless integration with Pinecone for vector database management, LLM-optimized tool search and retrieval, and capabilities for cross-server tool orchestration and invocation, all designed to enhance performance for MCP systems.

Aggregator

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Key Features

Use Cases